• Working with a team for revamping the Stony Brook University Smart Transit system used by students of the University.

• Built the front end for the smart transit web app using React.js, react-router and leafletjs.

• Integrated with SBU REST APIs following their Swagger doc.

• Setup the build system of the react app using Webpack and Babel.

• Currently working on backend APIs written in Python (Flask). Graduate Research Assistant, Stony Brook University, New York Jan ‘18 – May ‘18

• Worked under Prof. Shan Lin with team from Carnegie Melon University to design an Intelligent HVAC system for Smart Building.

• Extracted parameters like Humidity, Air Temperature, Air Velocity from EnergyPlus for the set time interval using MATLAB, SQLlite and OpenBuild to calculate the comfort level of people in a room with UC Berkley’s CBE Thermal Comfort Tool and verified the comfort level with ASHRAE-55 standard. CAPGEMINI, Software Engineer, Mumbai, India July ‘15 - July ‘17

• Enhanced a Point of Sale(POS) single-page web app for sales of Mercedes-Benz to help the clients to customize Mercedes cars or buy the existing ones and for sales representatives to keep track of all their clients and their purchases.

• Developed the front end using xHTML, JavaScript, Ajax, JQuery and the backend in JAVA, JSF and Hibernate with a support of ten different languages.

• Migrated an entire application from JSF 1.2 to JSF 2.2 and was part of a critical go-live.

• Worked on Jasper reports using JRXML to generate documents related to financial documents, order and offer of cars. ACADEMIC PROJECTS

• Developed a targeted ATPG tool using PODEM which can detect test patterns for every single stuck-at fault in combinational circuits. Optimized the PODEM further by applying Event driven simulation to reduce time taken by ATPG from 20 minutes to 5 minutes.

• Performed fault collapsing technique to reduce the number of stuck at faults for testing, which further reduced the running time to 30 seconds for considerably large benchmark circuits. Web Scraping of IMDB Website (Python)

• Scraped the data of the IMDB Website for the list of top 200 Movies from 2000 – 2017 in each year sorted according to number of votes.

• Performed analysis on acquired list to generate the Top 10 Movies list for a certain Year and Genre.